Florian Kirchbuchner

Computer Vision and Pattern Recognition · 2021

A researcher in the Science corpus: 1 paper; trusts 20 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Florian Kirchbuchner trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Kaiming He
  2. Jiankang Deng

Papers from Florian Kirchbuchner's perspective

Ordered by how strongly the researchers Florian Kirchbuchner trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  2. ImageNet classification with deep convolutional neural networks
  3. Going deeper with convolutions
  4. Gradient-based learning applied to document recognition
  5. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  6. ImageNet: A large-scale hierarchical image database
  7. ImageNet Large Scale Visual Recognition Challenge
  8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  10. FaceNet: A unified embedding for face recognition and clustering

Their papers